{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Copy of death_rate_colab.ipynb","provenance":[{"file_id":"https://github.com/jianxu305/DXY-2019-nCoV-Data/blob/master/death_rate_colab.ipynb","timestamp":1582344206178}],"collapsed_sections":[],"mount_file_id":"1RAbKz5qx9bujAeEc8uHvqUKKnWpG1uog","authorship_tag":"ABX9TyMqHOBz72PnrqS2uu2TD+DL"},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"code","metadata":{"id":"eKslLBFNsqph","colab_type":"code","outputId":"f65ee35f-7269-40e7-d5a0-e541d98c3295","colab":{"base_uri":"https://localhost:8080/","height":136},"executionInfo":{"status":"ok","timestamp":1582343900953,"user_tz":360,"elapsed":3462,"user":{"displayName":"","photoUrl":"","userId":""}}},"source":["! git clone https://github.com/jianxu305/nCov2019_analysis/\n","\n","import sys\n","import os\n","os.chdir('/content/nCov2019_analysis/src')\n","\n","sys.path.append('/content/nCov2019_analysis/src')"],"execution_count":2,"outputs":[{"output_type":"stream","text":["Cloning into 'nCov2019_analysis'...\n","remote: Enumerating objects: 198, done.\u001b[K\n","remote: Counting objects: 100% (198/198), done.\u001b[K\n","remote: Compressing objects: 100% (151/151), done.\u001b[K\n","remote: Total 198 (delta 104), reused 116 (delta 47), pack-reused 0\u001b[K\n","Receiving objects: 100% (198/198), 12.48 MiB | 19.42 MiB/s, done.\n","Resolving deltas: 100% (104/104), done.\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"LYgkJCsgqP14","colab_type":"code","colab":{}},"source":["import pandas as pd\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import utils   # some convenient functions\n","import matplotlib.font_manager as mfm\n","import datetime\n","\n","%load_ext autoreload\n","%autoreload 2"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"yth1KlwfslkQ","colab_type":"code","outputId":"38e69a5b-5828-4f4c-ec29-733f42363107","colab":{"base_uri":"https://localhost:8080/","height":68},"executionInfo":{"status":"ok","timestamp":1582343907909,"user_tz":360,"elapsed":992,"user":{"displayName":"","photoUrl":"","userId":""}}},"source":["data = utils.load_chinese_data()"],"execution_count":4,"outputs":[{"output_type":"stream","text":["Last update:  2020-02-22 10:56:37.799000\n","Data date range:  2020-01-24 to 2020-02-22\n","Number of rows in raw data:  50467\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"mWkO9PYiswpO","colab_type":"code","colab":{}},"source":["daily_frm = utils.aggDaily(data)"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"XjiQu56eMgvQ","colab_type":"text"},"source":["## 1. Sanity Check\n","### 1.1 Take a Brief Look at the data"]},{"cell_type":"code","metadata":{"id":"z3cm-ThnMkVW","colab_type":"code","outputId":"02cbffd7-7123-4fc2-c1da-3702d8123b65","colab":{"base_uri":"https://localhost:8080/","height":555},"executionInfo":{"status":"ok","timestamp":1582344028046,"user_tz":360,"elapsed":1346,"user":{"displayName":"","photoUrl":"","userId":""}}},"source":["fig = utils.tsplot_conf_dead_cured(daily_frm, title='Confirmed, Dead, Cured within China', figsize=(12, 8))"],"execution_count":6,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAx0AAAIaCAYAAABF6yCfAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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FlIX0JsH/Mcc1C2hK2dccqSM8O6c3i5C+36tWrb7eK9o7Kzs6mQ4cOFS5HEqPrLSIiqVLS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\nAAAAAElFTkSuQmCC\n","text/plain":["<Figure size 864x576 with 3 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"tMaiFAL8oyl2","colab_type":"text"},"source":["### 1.2 Confirm the ~2% mortality rate"]},{"cell_type":"code","metadata":{"id":"lu49nXo6ouzt","colab_type":"code","outputId":"dbe22355-01d9-4b4f-d43f-43eb36eec13b","colab":{"base_uri":"https://localhost:8080/","height":405},"executionInfo":{"status":"ok","timestamp":1582344033962,"user_tz":360,"elapsed":580,"user":{"displayName":"","photoUrl":"","userId":""}}},"source":["avg_frm = daily_frm.groupby('update_date').agg('sum')\n","avg_frm['mortality_rate'] = avg_frm['cum_dead'] / avg_frm['cum_confirmed']\n","ax = avg_frm.plot(y='mortality_rate', grid=True, figsize=(12, 6), marker='o', title='Mortality Rate within China')\n","plt.gca().set_yticklabels(['{:.1f}%'.format(x*100) for x in plt.gca().get_yticks()]) \n","plt.show()"],"execution_count":7,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAtIAAAGECAYAAAAbVcfdAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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FhER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\nN+zcz+x1u8jaX3Ya8+iIMAqLHU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size 864x432 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"2sFu8Jp5NIG2","colab_type":"text"},"source":["## 2. Mortality Rate Disparity"]},{"cell_type":"code","metadata":{"id":"4OefTkNUvQ4t","colab_type":"code","colab":{}},"source":["import plotly.express as px\n","import chart_studio\n","import chart_studio.plotly as py\n","import plotly.graph_objects as go\n","from plotly.subplots import make_subplots\n","api_key  = ''  # use you own key\n","user_name = ''  # use your own user name\n","chart_studio.tools.set_credentials_file(username=user_name, api_key=api_key)"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"L-ng3hnh-Sot","colab_type":"text"},"source":["### Split the mortality rate into three regions:\n","Wuhan, Hubei Province except Wuhan, and China except Hubei Province"]},{"cell_type":"code","metadata":{"id":"nNbfSShH-mlE","colab_type":"code","colab":{}},"source":["daily_frm['region'] = np.where(daily_frm['city_name_en'] == 'Wuhan', 'Wuhan', \n","                  np.where(daily_frm['province_name_en'] == 'Hubei', 'Hubei_ex_Wuhan', 'China_ex_Hubei'))\n","region_frm = daily_frm.drop(columns='zip_code').groupby(['region', 'update_date']).agg('sum')\n","region_frm['mortality_rate'] = region_frm['cum_dead'] / region_frm['cum_confirmed']"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"a95HxM_hErBm","colab_type":"code","outputId":"914e315b-b846-480f-ba94-25b9235a674d","colab":{"base_uri":"https://localhost:8080/","height":542},"executionInfo":{"status":"ok","timestamp":1582303032446,"user_tz":360,"elapsed":1221,"user":{"displayName":"","photoUrl":"","userId":""}}},"source":["fig = px.bar(region_frm.reset_index(), x='update_date', y='new_confirmed', color='region', \n","        title='Daily New Confirmed Count in Different Regions')\n","fig.show()"],"execution_count":9,"outputs":[{"output_type":"display_data","data":{"text/html":["<html>\n","<head><meta charset=\"utf-8\" /></head>\n","<body>\n","    <div>\n","            <script 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Better Estimates of Mortality Rate"]},{"cell_type":"code","metadata":{"id":"uAO_44oA63KZ","colab_type":"code","colab":{}},"source":["lag_frm = region_frm.copy()\n","lags = [0, 4, 8]\n","for lag in lags:\n","    lag_frm['cum_confirmed_lag' + str(lag)] = lag_frm.groupby(['region'])['cum_confirmed'].shift(lag)\n","    lag_frm['mortality_rate_lag' + str(lag)] = lag_frm['cum_dead'] / lag_frm['cum_confirmed_lag' + str(lag)]\n","\n","# remove earlier dates to improve visually due to the lags\n","lag_frm = lag_frm.reset_index()\n","lag_frm = lag_frm[lag_frm['update_date'] >= pd.to_datetime('2020-02-05')].set_index(['region', 'update_date'])"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"tGV6Qo5HI01K","colab_type":"code","outputId":"d836336c-639a-45f7-b584-02f1d605edd5","colab":{"base_uri":"https://localhost:8080/","height":542},"executionInfo":{"status":"ok","timestamp":1582309899044,"user_tz":360,"elapsed":763,"user":{"displayName":"","photoUrl":"","userId":""}}},"source":["fig = go.Figure()\n","for region, color in zip(['Wuhan', 'Hubei_ex_Wuhan', 'China_ex_Hubei'], ['green', 'red', 'blue']):\n","    for lag, line_style in zip(lags, ['solid', 'dash', 'dot']):\n","        fig.add_trace(go.Scatter(x=lag_frm.index.get_level_values('update_date'), \n","                                y=lag_frm.loc[region]['mortality_rate_lag' + str(lag)],\n","                                line={'dash': line_style, 'color':color},\n","                                mode='lines',\n","                                name='lag ' + str(lag) +', ' + region))\n","fig.layout.yaxis.tickformat = ',.1%'  # 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\"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Mortality Rate Using Different Lags in Different Regions\"}, \"xaxis\": {\"title\": {\"text\": \"Date\"}}, \"yaxis\": {\"tickformat\": \",.1%\", \"title\": {\"text\": \"Mortality Rate\"}}},\n","                        {\"responsive\": true}\n","                    ).then(function(){\n","                            \n","var gd = document.getElementById('6fab9ea6-74be-4ed8-86d4-73b07075360c');\n","var x = new MutationObserver(function (mutations, observer) {{\n","        var display = window.getComputedStyle(gd).display;\n","        if (!display || display === 'none') {{\n","            console.log([gd, 'removed!']);\n","            Plotly.purge(gd);\n","            observer.disconnect();\n","        }}\n","}});\n","\n","// Listen for the removal of the full notebook cells\n","var notebookContainer = gd.closest('#notebook-container');\n","if (notebookContainer) {{\n","    x.observe(notebookContainer, {childList: true});\n","}}\n","\n","// 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upload"],"execution_count":44,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'https://plot.ly/~jxu1/106/'"]},"metadata":{"tags":[]},"execution_count":44}]},{"cell_type":"markdown","metadata":{"id":"ZrwXA-qBNhTV","colab_type":"text"},"source":["### 2.1 Compare mortality rate by province"]},{"cell_type":"code","metadata":{"id":"amaeHBiu0fTo","colab_type":"code","colab":{}},"source":["province = daily_frm.groupby(['update_date', 'province_name_en']).agg('sum')\n","province['mortality_rate'] = province['cum_dead'] / province['cum_confirmed']"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"oJ3jBErRpbqC","colab_type":"code","outputId":"f3c10e41-c0f8-40ee-93ab-9a9eaa51bf25","colab":{"base_uri":"https://localhost:8080/","height":499}},"source":["fig = utils.cross_sectional_bar(province.loc[(datetime.date(2020, 2, 16), ), :], \n","                                None, col='mortality_rate', groupby='province_name_en', \n","                                title='Fig 1. Mortality Rate of Each Province as of 2020-02-16',\n","                                figsize=(12, 8))\n","plt.show()"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAwgAAAHiCAYAAABMRevaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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Go1FhzY\n2uhiRC+l/ppf6rC5pf4ihoZhHyAA2H4UOK6DpO/U7XMacFpd2rlQvUawfV75NvBLYFLdfkd1cs6z\ngLPqNv17L4sfERERETFoRkIToz4pQcGK74iIiIiI4SwBQkRERERErJAAISIiIiIiVkiAEBERERER\nKyRAiIiIiIiIFZo+QGibW0DSqpJWKctNf10REREREY3QdMOcSnoTMINq1uNvAGcCNwH/Dzha0muB\n/5Jk4F229+1GnrsDM23/Z1n/I3C47T8OzFV0bNGSZUw+9tLBPGX0s1ktS5mROmxaqb/BtSDzvkRE\nDElNFyDYnivpamBjYCPbN5Xt8yU9AMyy/aikscDvu5ltDbirbn1/qlmRIyIiIiJGlKZsimN7OXAQ\nMFXSRwEkHQacXyZFw/Yi2w91M79nbN9Zt76gnCMiIiIiYkRpujcIbWz/Q9I7gSskjQb+1vY2AUDS\n9sChtt9X0o8BHgQmA1sDmwC72n5E0quA421Pl7Q21azLl9u+StI4YBawCNgZOMj2g5JeAXycambl\nVuDNwNm2v1zOP6qk/6Gc81rbfx7YuxIRERER0Tdq9gmCJf038GHglbYfLttE9XC+q+1WSVsBFwDn\n2P7vss/JVEHFVyQdAsy2PVnSZsBFwIds1ySdBZxp+3pJnwdutf09SacA+wI72r5P0gbALbY3Lvkf\nBmxg+/Ol0/R84OfAzbbPqyv/TGAmwPjxE7aZffo3B/qWxQCaOBYeWdToUkRvpf4GV8vG6/R7ngsX\nLmTcuHH9nm8MjtRfc0v9NZdp06bNsz21o7SmfYMAUPoZAFwM/J+kt9heYtuSfgTsCmD7Zklzgbl1\nh98KvKykf0vS7LL8F0nX1+33Nds3StoEeAXP91X4KjDV9n3luMckLak7bkvg5pK2XNLTwPdt31h/\nDbbnAHMAJm06xafOb+oqGfFmtSwlddi8Un+Da8GBrf2eZ61Wo7W1//ONwZH6a26pv+GjKfsg1DkO\nOBU4DFgfOK2Hx6sb+9wk6Rhge6AnTYQuAbYDkLQOMA64s8sjIiIiIiIarGkDBEkfA35s+wnb/wL2\nA2ZImtHPpzqaqinWj6neOEjSat047nfA05LeBewGvM32M/1ctoiIiIiIftV079IlTQP2ppoH4VFJ\nT9leALyEqp3/HEkTy+6TJG0HLAdagAPKUKgAbwE2kjTF9t11+b8Z2Ap4q6RbSr4tku6jmm/hY8Cj\nwObAFEnTgZ8CuwPjJR0EnEfVbOjXVEHM4u5c29jRo7gj44I3tVqtNiDNJmJwpP4iIiKaMECw/Rvg\nN8CRpfOvyvZfUz2QU0YtWg6cDIwBFtvepnRexlXP7Pe0z7p8X0c1ytGosu/H2u13RjnHJbZPkaSS\n34VUzYgo6UdS9Y04VtJjZfP5tk/p4y2IiIiIiBgwTRcg1OtsrgLb9Z2Fn6vb3uGQTZLWoBoCFdtt\n+y9dybndWZ6SVgU+STUk6g/bvDQAACAASURBVF1l29rAOZK2tH1LV3lHRERERDRK0/ZB6GdTgbP7\nMb9XAK9oCw4AbD8FXA38tR/PExERERHRr5r6DUJ/KM2ONrH9rf7K0/atki6W9CHgHqq3EaOBS20/\n2V/niYiIiIjobyM+QChNhL4/APme2d95RkREREQMtDQxioiIiIiIFRIgRERERETECsM2QJA0qgx3\n2rY8pi5tjKRRZXn1RpUxIiIiImKoGc59EMYC0yWdDRwAzAUeKmmbAF+StDHwCeCqxhTxhRYtWcbk\nYy9tdDGiD2a1LGVG6rBpDZf6W5AJFyMiog+GbYBge6GkK8vy+e3S7pE0H3ja9pAIDiIiIiIihoJh\n28QoIiIiIiJ6bti+QeiJ0h/hncATwARgM+AzwLpUE6idCuwNvAG43/b0ctxE4Aiq2ZrfDOxj+xlJ\n2wLvAv4MbFfSPmP7R4N5XRERERERPaVqGoDhSdJk4F7ggx0k7wE8anuGpI9RBUvzS9puwMnAtsAP\ngbfanlsmVbsWeL/t+ZIuB2bYfljS94D/BeYBZwGbAzvbflzSq4BzbW/TQRlnAjMBxo+fsM3s07/Z\nT1cfjTBxLDyyqNGliN4aLvXXsvE6jS5CwyxcuJBx48Y1uhjRS6m/5pb6ay7Tpk2bZ3tqR2kj4g1C\nR5OWSdoImFxWpwMH2769rF9evu+X9KDtuSUfS7oNWL+kH1eCg82BjYHRtp+VdBZV4PB4Oe5WSW3H\ntC/bHGAOwKRNp/jU+SOiSoatWS1LSR02r+FSfwsObG10ERqmVqvR2tra6GJEL6X+mlvqb/hIH4TK\nasCre7C/yvetko6nGhVpQTePiYiIiIgYshIgVC4FZkvaAEDSJEndCRi+DNwKXAlMqg7VagNXzIiI\niIiIgdX879I7UZr9tHUm3h+43PbTZb0FmAq8VNJuwIlUbwFulnQ98EvbX5P0n8AGko4AfkDVr2BL\nYE9JNwMbAfsCBn4PfB44Dtgd2KbkfRWwDzBB0m62f95ZmceOHsUdGb+8qdVqtRHdvKPZpf4iIiKG\ncYAA/JXqwf8EYHVgcV3a3cBewHJgNLDE9sEd5PEz22tJkqve3NcAW9el71u3/H9QvUIAfmv7mLrj\nzi2fiIiIiIghbdgGCLafrVtd1C6tfv25LvJYXr67PdRT/b49OS4iIiIiYihIH4SIiIiIiFghAUJE\nRERERKyQACEiIiIiIlZIgBARERERESskQIiIiIiIiBWG7ShGfSVplO1lZXlV20vr0tYGvgY8a/vQ\n/jrnoiXLmHzspf2VXTTArJalzEgdNq3Brr8FmfckIiKGoLxB6NzLJX1E0lJgV0mjJS2Q9BLbTwE/\noppDAUkbS7pX0uiGljgiIiIioo8SIHTC9t3ARVRvCX5mewnwFtsPll0W1u3+IPDWsk9ERERERNNK\nE6MesH1PJ9sNdJgWEREREdFM8gahmyRtKOkcSZM7SHuZpJ/Xre8m6b8kfVTSuZLulLTjYJY3IiIi\nIqI38gah+14C7AIc30HaZOAtAJLGA0cCS4DpthdJ2q1su6r9gZJmAjMBxo+fwOyWpe13iSYycWzV\n0TWa02DXX61WG7RzjRQLFy7MfW1iqb/mlvobPhIgdJPtmyTd3knaVZIeLsuPSvohMNn2orLLrcD6\nnRw7B5gDMGnTKT51fqqkmc1qWUrqsHkNdv0tOLB10M41UtRqNVpbWxtdjOil1F9zS/0NH2liNHjU\n6AJERERERKxMAoSVc6MLEBERERExWNIWomsCnpK0CvA2YDNgd0lzgX2BFklvBCYA4yXtDdxA1R9h\nkqQdgNuA/YDNJL3R9tWdnWzs6FHckYmTmlqtVkuzkSaW+ouIiEiAsDKrAvfbXi7pN8Cksm257Q8D\nlOBhFLAW1cRpS4D32rYklSFQTymfiIiIiIghLQFC19YGLgGwvbhse8FkaLaXA8vL6uJ2aWmeFBER\nERFNJX0Q2pE0StKEsroNcFYjyxMRERERMZgSILzYlsCfJX0a+JPthxpdoIiIiIiIwZImRu3YvhHY\nsNHliIiIiIhohLxBiIiIiIiIFRIgRERERETECmliNIQsWrKMycde2uhiRB/MalnKjNRh0+pp/S3I\nvCURETEMDbs3CJJ2lXSKJEv6gKSdJB0o6VuSXr2SY/eR9JOyLEn3SHppWf+YpNMG4xoiIiIiIhpl\n2L1BsH2ZpNuAWcAVthcASNoQOBvYvovDLwOuKfm4zIx8f0n7FsPwfkVERERE1BsRD7ySRgGtwE+7\n2s/2ImBR3frNdctPDlT5IiIiIiKGCg3HyX4lTQbuBY4C/gkcAIwDDrV9u6TxwJ7Ao8DmwCO2z5W0\nfdnnfZLWBo4DLgd+C+wM7GT7aElrAieXtNcD21IFW7vYfraUYU+qmZgfBza0/Z1OyjoTmAkwfvyE\nbWaf/s3+vh0xiCaOhUcWrXy/GJp6Wn8tG68zcIWJXlm4cCHjxo1rdDGil1J/zS3111ymTZs2z/bU\njtKG+xuEn5YmRudIOgS4tvRD+DLwfWAJcCewq6TzgB2BzcqxLwf2AK4AVgN2AdYtaVOBdwDX2v4k\ngKTzgbcBP5O0PnCC7a1K2omSvg0stv2B+gLangPMAZi06RSfOn+4V8nwNqtlKanD5tXT+ltwYOvA\nFSZ6pVar0dra2uhiRC+l/ppb6m/4GHadlDtj+1tUv+bvA7zJ9kW2L7d9se0PunqV8qO6/W8G5pXl\nZ4EL69KuAuYDc+tOcSuwflmeAvyrLu0+4Kn2wUFERERExFAzYgKE4mlAwEalmVF/U/m+BVijNFOC\nqmP0lQNwvoiIiIiIfjXcA4Q12hZK/4J1gXOBq4FTS+dlJL1JUn82mnsOOAn4tKS3A+favqgf84+I\niIiIGBDDrrG0pC2B95fVb0s6FxhF1eznTbb/Kekg4BzgTknXluU1genAJEnb2b6uLs/JVJ2aXylp\nC2ACMBk4RNI3gPFUbwmmSPoFsCVwEHCw7b93t+xjR4/ijky81NRqtVrapTex1F9ERMQwDBBs3wIc\nWT6d7bOAatjTFSSNBk4FvgSMqd8deBA4piyPBv5se7IklfweoOrE3JbXQ1QBw22S7qFqenQn8DHb\nj/TtCiMiIiIiBs6wCxB6y/aSutXnyvcawIO2F9elLa47prMxYqcD99neAFbMwzAd+ATV0KsRERER\nEUNSAoROlLcDz9i+qxeHz6IaIhUA28sk3UDV1CkiIiIiYshKgNC5NwOf7eWx7weOlDSP54c7XW77\nvH4pWURERETEAEmA0Iky10Fvj72FaqjTiIiIiIimMtyHOY2IiIiIiB4YMQGCpFFlpKK25TF1aWPq\n5kRYvYs8jpb084EvbUREREREY4ykJkZjgemSzgYOAOYCD5W0TYAvSdqYaqShzpoXXUQ1DGqPSNoW\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9KnAIgKQdgDXK9s2BTdqCg3Lc1cAbJU20fQHwoO25Jc3AbcD65a3AhXXHXQXMB+bWnfdW\nYP2yPAX4V13afcBT7YODiIiIiIihpicBwlHAxcBmkq4Gvgt8eEBK1UOl6RAAtp8Alkg6BXiQ5x/U\nlwNLOzjcVM2NOs2+J0Up37cAa0hau6xvD1zZg3wiIiIiIhqi220hbN8gaUeqX+IF3GF7yYCVrJsk\nbQwcULcu4OfA26mCg3VL86IFwIOSXmH7zrLvDsD1tv/Wz8V6DjgJ+LSkXwHn2v71yg4aO3oUd2SM\n+KZWq9WGdBOaiIiIiJXpdoAgaRTw/9m79zir6nr/46+3iIiOWgJmajQqiqV4A8vUalAz81J2vNXx\naGZKpXnP1DoZdrqoR0uzi6Glhd0w71rqz3RMj5mh4o0kU8lQ08ISpyAR3r8/1nc4+0wDzIaZ2ezh\n/Xw85rHXWt/1vez9/Wd9Zn0vewGtJd8ekrD9lT5qW23d44Ddyum+kv4IDAI2oHqzcQbwWkm7Uy23\n+hrgGOAu4B7gR8BRwL8BH5c0lertyVigc2Lz+4Bhko4p94+mmtuwr6SXgH2BLSRtBYyg+h2OkPRt\nYDjVW4JRkm4p+Q4FPmz7hb76XSIiIiIiels9symvB+ZRjb1f2DfN6Z7tqcBU4OyuaZK+VQ4vB1az\n/U9gZM0tN9ccz6EKJjpdU3N8ve21JKnMP/gVsH2pYzXgFKrhSIOBR223lrcV2H6GahJzZ5ueowoY\nfivpSao3Lr8DTrT9fL3fPyIiIiKiv9QTIGxke+s+a8kysl07r+Cfy1HOwvL5L+u+2n6l5vSVmuuL\nWyP2IOBp28Ng0duXg4BTqd54RERERESskOqZpPxzSXv0WUsGlpOBGzpPbC+g2u35/oa1KCIiIiKi\nB+p5g3APcHWZ8DufatiMba+95GwrpSOB4yTdR80qSrYvb2CbIiIiIiKWqp4A4StUuwY/vIShNQHY\nfohqqdOIiIiIiKZSzxCjPwKPJDiIiIiIiBi46nmD8CTQLunn1EwG7o9lTiMiIiIion/UEyA8Vf5W\nY8k7DzdMmR9xCLApVVvnUO2XsAvwnO1/WSa1mzJ+Axxt+zd92dbuzJ2/gNbTbuzvaqMXnTzmVQ5v\noj6cmY35IiIioot6dlI+sy8bsrwkrQ1cB1xne2KXtKuBC3pY1IHA073buoiIiIiI5lDPTsojgE8B\nWwKrd163vWsftGtZfBuY092QJ9sLJB3fk0Jsz+zthkVERERENIt6Jin/AHgM2Bg4E5gJ9PswnO5I\nWo9qI7IrFndPCRIGSzpZ0sySb1NJn685X1vSlyW9s5x/QNLE8vnvkn4sadOSNk7SKZL2kHRIOR4k\naS1J50pqL/eNkXRR53lERERExIpMPV2USNJ9tsdKeqhzR2VJv7G9Q5+2sGdtextwN7CH7f9Xc311\nYDywDTCOavOy3wOX224t97QC7bZby8P/tcAnbLdLerftm8t9ZwNr2D5W0kbAz4Htbc8v6Z8BXrV9\ntqQ2YKLttpL2f867tH0CMAFg+PARY884/+Je/GWiv71uKDw/t9Gt6LkxG67T6CasUDo6OmhpaWl0\nM2I5pA+bW/qvuaX/msv48ePvsz2uu7R6JinPL5/PSdobeBZYd3kb10tml8/W2ou251HtAD0X+LLt\nA0pA0C3bT0iaWnPeGRwcBuwI7F6S9gUe6gwOipuAy4GlToTuUuckYBLAyE1G+byH6+mSWNGcPOZV\nmqkPZx7S1ugmrFDa29tpa2trdDNiOaQPm1v6r7ml/waOep5kviBpHeBk4EJgbeDEPmlVnWz/TtID\nwEclfdf2giXdXk/ZknYCzgB2qgkIFgKvdrl1If+7ulP2ioiIiIiIptTjOQi2b7D9ku1HbI+3Pdb2\ndX3ZuDodCmwEXCSpa+AzCugc+DEbWFvS4HI+lmop1H8haSTwI+CDtl+QtL6kt1INVdq6pgyAvYHL\nyvGfgfVq0rZfXB0RERERESuSelcxOopqGM+ifLaP6P1m1c/2o5K2onrD8UNJdwPPAGsA2wL7lPs6\nJF0ATJV0L9Wcg79KOhB4nmq+wm6SfgdcDzwMbCnpLcBHgH1sPyvpo8Apkh4EhgN/pyylanu6pLtL\n+fcA9wKrSNrd9q2L+w5DBw9iRtalb2rt7e0ZthMRERFNrZ4hRtcCdwK3AksawtMwtv8CnN5N0ve6\n3Hcm1UpMnW4AkDSEmv/2296mSznfqCnjXqoH/8W15cguly5fSvMjIiIiIhqungBhDdun9llLVgC2\n/1kOu84viIiIiIhYKdSzD8INkvbqs5ZERERERETD1RMgHE8VJMyVNEfSy5Lm9FXDIiIiIiKi//V4\niJHttZaULmlL248uf5MiIiIiIqJR6nmDsDSTe7GsiIiIiIhogN4MENSLZUVERERERAP0ZoDQdLsH\nS9pY0u2SWhvdloiIiIiIFUE9y5yukCTtCmwH/A0YDbxs+78kXQVMtn31ErK3Alv0fSt7Zu78BbSe\ndmOjmxHL4eQxr3J4P/bhzGysFxEREb2sNwOEV3qxrB6RNBw40fa+Nde+UA6PA15YUn7bt0ua0YdN\njIiIiIhoKj0eYqTKf0g6o5yPlPSWznTbO/ZFA5diQ2CMpNfXXDu7tGeW7X4PWiIiIiIimlk9bxC+\nCSwEdgU+D7wMXAnsB5CF0wAAIABJREFU0Aft6qmHgAeBRyWdDVxo+2VJqwMfA2bbnixJwOnAYGAk\n8HZgf9sPl3I2lvRRYCzwD+AAqknXxwHH2m6VtCnwIeAw260AkvYBtgJGAU/Y/rKkwcApwLNUQ5i2\nBzYC3mP7+b79OSIiIiIilo/sns0tlnS/7e0lPWB7u3LtQdvb9GkLl96uVYBjgc9SDXM6CbgD+CHw\nPduXlYf/d9g+pOTZCXjM9ouS2oFrbJ9f0n4EfN/2z8vk5faagGDRuaRRwFm2DyhBwXTbm0naBrgK\nuMz2f5V85wB/tH1hN+2fAEwAGD58xNgzzr+413+j6D+vGwrPz+2/+sZsuE7/VbYS6OjooKWlpdHN\niOWQPmxu6b/mlv5rLuPHj7/P9rju0up5gzBf0iDKakWSRlC9UWgo2wuBCyRdSvWWYDKwB1WQ0Ond\nwLU1ee7uUsw1NcczgPV6UPXfgWNKgNJG9XYC2w9KuhO4s+be6cAbF9P+ScAkgJGbjPJ5Dzf9vPGV\n2sljXqU/+3DmIW39VtfKoL29nba2tkY3I5ZD+rC5pf+aW/pv4KhnmdOvAVcD60n6InAX8KU+aVUP\nSdpB0loAtufYPh34b6pVjWq9ArymnqLL52Jfr9h+DhgGnEU1zKmnZUZERERErLB6HCDY/gHwKeDL\nwHPAfrav6KuG9dBo4IQu1wYDv+xy7UrgY5JeAyBpDUlb9qD82cDaZQgRVHMUBpUy1gKmAJ8DhlaX\ntGp5oxARERER0ZR6PBZC0o7Ao7a/Uc7XlvRW27/us9Yt3QPAgZK+CdwPDKF6s2FgJ2BDSbfYvkLS\nJsDtkp4A/gB8vuyh8AbgCEmXUP0eO1NNWr7F9rOSLgCmSrqXapjSXyUdCNwLDAc+DvwG6AAuAL4P\njAEOlvRMaeeuwPqSRtn+/eK+zNDBg5iRde2bWnt7e4b9RERERFOrZ7D0t6hW5OnU0c21fmX7UeB9\nXa9LGkI172CV8oftsylLoNbcd4ftTcsqRyrzGd7VpY4zgTNrLt1Qc7x+zfGWpUzZHlvKxNUs8MOW\n7RtGRERERPSvegIEuWbJI9sLJa2QM2pt/7McLih/i7tvQfk0S5hvUGfdrv2MiIiIiGgm9YyXf1LS\ncZIGl7/jgSf7qmEREREREdH/6gkQPkY1rv8ZYBbwVsr6/RERERERMTD0eIiQ7ReAD/RhWyIiIiIi\nosHqWcVoBHAU0Fqbz/YRvd+siIiIiIhohHomGV9LtTvwrSxh4m9ERERERDSvegKENWyf2mct6UeS\n3gm8z/ZJdeTZGrjc9tZ91a658xfQetqNfVV89IOTx7zK4f3YhzOzb0ZERET0snomKd8gaa8+a0n/\n2g34d0mD6sizKbDZslRWVn2aKWmDZckfEREREdFf6gkQjqcKEuZKmiPpZUlz+qphfUXSUGAm8Geq\nzdR6xPbVwPPLUqft+cCutp9dlvwREREREf2lnlWM1urLhvSj9wK3ACOAQ4Gf9UeltrNnRERERESs\n8LS0DX8lbWH7MUnbd5du+/4+aVkfkfQZ21+UtBHwGLCB7TmSVgE+BLwWGAJsC4wBDrA9veSdCewH\nHAK8DXjY9sclrQV8Dhhnu03SGOAYYItyvh5wDjDR9swu7ZlA2U9i+PARY884/+I+/gWiL71uKDw/\nt//qG7PhOv1X2Uqgo6ODlpaWRjcjlkP6sLml/5pb+q+5jB8//j7b47pL68kbhJOoHmDP6ybNwK7L\n0bZ+Jel1wIaS9iuXngQOBL4DvBE4GrgfONr2AklHAx8BTq4pptX2KaW8X0l6k+3fSroBGAdg+2FJ\nPwYmljwbAHvWnC9iexIwCWDkJqN83sP1zBuPFc3JY16lP/tw5iFt/VbXyqC9vZ22trZGNyOWQ/qw\nuaX/mlv6b+BY6pOM7Qnlc3zfN6fPHUz1X/wXACQNAw4DvmP7KUk3AjNtdy7jOh3YobYA29fUnM4A\n1gN+u6RKbU+T9FgvfYeIiIiIiD7T40nKkh6SdLqkTfuyQX1sZGdwUFwJvEXSG5eQR0spszN9yWO1\nIiIiIiKaQD2rGO1LtUHaFEm/kfRJSSP7qF29rswLmFF7zfbfqCYpH9oLVfyZ6m1Cp+2BepZRjYiI\niIhouHpWMfoD1UTbcyRtBnwWOJsV/CG47HXwduCTwHWSNrX9REl7K/AKcIykBVQTj7eSNA34C7AP\nsK2kbYBW4DWSjgGmAK8HtgH2kvSg7emS7pZ0L3APcC+wiqQ9qN4ybArsLelS2//orq1DBw9iRja+\namrt7e2ZFxARERFNra7ZlGUozsHlbwHwqb5oVG8qk43vtN0uSdQMGbL9a+CDACXtLNuWJFfLO32y\n815Jj9h+TVntCNt/BrbrUteRXaq/vORdDRhJ9Xsv7PUvGRERERHRS3ocIEj6NTAYuAI4sJnW9e+c\ndFwe+rudK+Ca9V5rj7spo+4HfNuvlMP59eaNiIiIiOhP9bxBOMz2jKXfFhERERERzaqeScp/kvQV\nSVPL33mSsktTRERERMQAUk+A8F3gZeCg8jcHuLQvGhUREREREY1RzxCjTW3vX3N+ZlntJyIiIiIi\nBoh63iDMlbRL54mknYG5vd+kfyXpNZIukPShPqzjdZJ+KinzLCIiIiJipVXPG4SPAd+vmXfwV6DX\nH9gl7Uq1fOjfgNFUw5qmUO058EBv19fJ9vOSPgfc2Fd1LM3c+QtoPa1h1Q84M7OnRERERETdehQg\nlLX/R9veRtLaALbn9HZjJA0HTrS9b821L9ieIam9t+vrxt/7oY6IiIiIiBVWj4YYlbX/P1WO5/RF\ncFBsCIyR9Pqaa2f3UV0REREREdFFPUOMbpX0SeAn1Pyn3faLvdieh4AHgUclnQ1caPvlmvQ1JJ0G\nbA9sDBxg+w8Akg4F1gfGAj+z/X1JawLnADcBbwPeQvWd97Q9T9IgqsDnRaohU++qbYyk9YEJwK+B\n1UoZ59p+UdJrge8A5wHvB3YCZtk+qCb/4VRDpQQstH1t7/xMERERERF9Q91sGtz9jdJTdLMLse1N\nerVB1XCmY4HPAq8AJ9n+saSJVHMSPlwe7j8KbGL7VEnvoAoWjpO0GfBN2++S9E7gKuAE25NL+VOA\nybavL8HGP21/taRtB1xtu7W041fA4bZ/W9J3Bv7T9nsk/RvwY2A323dKEnAPcKTthyW9Gfiq7XeX\nvJcDLwEv2f50zfedQBWEMHz4iLFnnH9xb/6cK7UxG/b/Nh0dHR20tLT0e73RO9J/zS992NzSf80t\n/ddcxo8ff5/tcd2l1fMG4c3A0cAuVIHCncBFy9+8/6sMZ7pA0qXA6cBkSc+X5JttzyvHM4Ady/Es\n4LOSVivtG1zKukPSw6WtnaYD65bjCcC7a9L+WnM8GtioMzgo5f2PpJ0lvc72VZKetX1nSbOk39aU\nvRXVm4lOs4DnO4ORmjInAZMARm4yyuc9XE+XxJLMPKSt3+tsb2+nra3/643ekf5rfunD5pb+a27p\nv4GjnmVOvwe8CfgacCFVwPC93myMpB0krQWL5jqcDvw31apG3WYp9z4JjAE+A0ztSVXlc3jNcVcL\ngVe7uW6q4UZLK/tOYJSkzif+scAve9C2iIiIiIiGqSdA2Mr2kbZvL39HUf2XvDeNBk7ocm0wS3mw\nlrQxcC5wJtV/8CVpSA/quxn46GLSHgeelbR5TT27AFNt/7EHZf+ZKoA6VdK+wOm27+tBvoiIiIiI\nhqlnPMv9kna0fQ+ApLfSs//W1+MB4EBJ3wTuB4YAdwH/AMYBW0l6hOrh/b3lfBtgDWADqof9GcBI\n4HRJdwCtwBGSvk31xmBHqv/s3wIcA3xP0vVUwcJCYJik99u+uswz+LikqVTB1FjgwPL931fuPQb4\nEVVwszWwr6QHgYOBbYGTbb/Uky8/dPAgZmTt/oiIiIhooHoChLHA3ZKeLucjgRlljL9tb728jbH9\nKPC+rtfLakP7lnH+g2wvAE7qctvImuONSz6VCcedQ5GeAfbsku89NfWsAny7lI/t54Azau69pub4\nettrlTpMNaF5+5qyvkP1mz0maRbV0KP7qCZdZ7+FiIiIiFgh1RMgdH2w7jedD+xdj3uQz7WfPbh/\nYR1lL1xK2UdTrYh0FICkwVRBzUeo5nFERERERKxwehwgdO43ED12LLBF54nt+ZLuB+YtPktERERE\nRGNlTc2+cyTwmRIUvFKuddj+nwa2KSIiIiJiiRIg9BHb7UB7g5sREREREVGXepY5jYiIiIiIAS4B\nQkRERERELNLUAYKk10i6QNKH+qm+NSSdLumz/VFfRERERER/a5o5CJJ2BbYD/ka1KdnLwBRgG6oN\n1vrDMKq9Dh6tN6Ok3wBH2/7N4u6ZO38BrafduBzNG3hmZuO4iIiIiH7VFAGCpOHAibb3rbn2Bdsz\nJLX3Vzts/1HSjVS7M9frQODppd4VEREREdFAzTLEaENgjKTX11w7u1GNWRa2Z9azEVtERERERCM0\nxRsE4CHgQeBRSWcDF9p+uSZ9DUmnUQ3/2Rg4oHNjN0mHAusDY4Gf2f6+pDWBc4CbgLcBb6H6Lfa0\nPa/k2xdYG3gRWM/292rqGyTpOGAHYAxwhO37S759gK2AUcATtr8saW3gdOAm23f09o8TEREREdFb\nZLvRbegRSatQ7U78WaqNx06y/WNJE6nmJHzY9jxJHwU2sX2qpHdQBQvHSdoM+Kbtd0l6J3AVcILt\nyaX8KcBk29dLWhe43fY2Je1LwOtLvb8CDivlvijp3VQBwsGSRgFn2T5A0mBguu3NJG0KXAt8ouyP\nUPu9JgATAIYPHzH2jPMv7qufsCmN2XCdRjehLh0dHbS0tDS6GbGM0n/NL33Y3NJ/zS3911zGjx9/\nn+1x3aU1yxsEyvCcCyRdSvXf+MmSni/JN3f+5x+YAexYjmcBn5W0GrALMLiUdYekh4E7a6qYDqxb\njkcB/6hJexpY0/bxkg4Hfmn7xZr61ivHfweOKcFMW019T0iaupjvNQmYBDByk1E+7+Gm6ZJ+MfOQ\ntkY3oS7t7e20tbU1uhmxjNJ/zS992NzSf80t/TdwNMUcBEk7SFoLwPYc26cD/021qlG3Wcq9T1IN\nAfoM0O0Denf5qIY0rVGGBkEVcNy2tHy2n6Na6egsqiFRERERERFNpSkCBKohRCd0uTYY+OWSMkna\nGDgXOJPq7YAkDelBff8Evgz8p6Q9qIYeXbu0TCWImQJ8Dhha6lu1vFGIiIiIiFjhNct4lgeAAyV9\nE7gfGALcRTUMaBywlaRHgMeB95bzbYA1gA2Aj1INBRoJnC7pDqqlSo+Q9G1gONVbglGSbgG2Bg6l\nmtfwQmcjJLUC7wA2ljQeuBs4CHijpJ2phjQNBz4O/AboAC7gf/dr2E3SQzXDk/6PoYMHMSPr/kdE\nREREAzVFgGD7UeB9Xa9LGgTsa9uSBtleAJzU5baRNccbl3yy3Sqpc2jQM8CeNeU+RxUw/FbSk1RD\niH4HnAh8pEt955S/TuvXHG9ZyhtCtcLSoPq/fURERERE/2mKAGFxygP6vxz3IJ9rP7txEPC07WGw\nKBA5CDjV9knLUN8/y+GrPc0TEREREdEITR0g9KGTgX06T2wvkHQ/eQMQEREREQNcAoTuHQkcJ+k+\n/ne504W2L29gmyIiIiIi+lwChG7YfohqqdOIiIiIiJVKlt+MiIiIiIhFEiBERERERMQiA3KIUVl1\naBXb88vxINuvlLTVgAVl4vHqtuc1tLE15s5fQOtpNza6GSuMmdkTIiIiIqLfDdQ3CEOBQyUZ2B8Y\nVpO2ETBF0j3AWxvRuIiIiIiIFdWAfINgu0PSbeV4Spe0JyU9DLxs+46GNDAiIiIiYgU1UN8gRERE\nRETEMlipAwRJa0k6V1J7OR8j6aKa8zUlfUPSvpK+JOlWSe2SVi/pLZI+J+lTkn4haYNyfXNJl0g6\nWNK3JD0q6aRGfc+IiIiIiJ6S7Ua3oU9IagWeAj7eTfI+wF9sHy6pDZhou63kW3Qu6Z3AVcAJtieX\n9CnAZNvXS7oEuMj2VElfBKbb/oGkc6nmPrzT9tOShgEP2d6wm3ZOACYADB8+YuwZ51/cez9Ckxuz\n4TqNbkLdOjo6aGlpaXQzYhml/5pf+rC5pf+aW/qvuYwfP/4+2+O6SxuQcxBq2b6o6zVJ6wOtPch7\nR5mvcGfN5enAuuX4G7YfkLQRsDnweLn+dWCc7adLObMlzV9MHZOASQAjNxnl8x4e8F3SYzMPaWt0\nE+rW3t5OW1tbo5sRyyj91/zSh80t/dfc0n8DR55GYVleoah8TpN0CtWbikd7r0kREREREY2xUs9B\nKP4MrFdzvj0wqId5P0k1TOunwBsBSRrSy+2LiIiIiOg3A/INgqTRwEHl+EDgJtsvl/MxwDjgDZL2\nAm4H7pZ0L3APcC+wiqTdgQVUQ5GOkPRtYDiwIzBK0i3ABsAYSU8D04ATgb8Ao8s9BwFXA3sDwyUd\nClzuxUz8GDp4EDOyOVhERERENNCADBCAPwBfAr4ArA68UpP2e2A/YCEwGJhv+8gu+S+H6nWA7VZJ\nArD9DLBnzX0ndsl3Qcl3g+1zS34D1wCZtRMRERERK7wBGSDYnldzOrdLWu35P5dSjms/66h/mfJF\nRERERDRa5iBERERERMQiCRAiIiIiImKRBAgREREREbFIAoSIiIiIiFgkAUJERERERCwyIFcxWhaS\nNgO+BWB790a0Ye78BbSedmMjqv4XM7MfQ0RERMRKqd8CBEmrAIcAmwJPAXOodizeBXjO9tn91Zbu\n2H5c0leBUxrZjoiIiIiIRuqXAEHS2sB1wHW2J3ZJu5qywdgK4O+NbkBERERERCP11xyEbwNzbH+l\na4LtBcDx/dSOiIiIiIhYAvX1Zr+S1gOeAw63PXkJ9w0GjgOOtd0qaVPgQ8BhtlvLPfsAWwGjgCds\nf7nkOwV4FmgFtgc2At5j+/mS723A1sATwObAt2xb0lDgM8DvqXZVPgAYZrut5NsMOAj4DbAWMAY4\n2/ZcSRsA5wKTgT2BdwC32z6p5jsdD8wAXgs8a/uObr73BGACwPDhI8aecf7FPfxl+9aYDddpdBOa\nUkdHBy0tLY1uRiyj9F/zSx82t/Rfc0v/NZfx48ffZ3tcd2n9ESC8Dbgb2MP2/6u5vjowHtgGGAfc\nQPWgfnlNQNAKtJeAYRRwlu0DSlAw3fZmkrYBrgIus/1fJd85wB9tXyhJwOPAm22/Uh7I9wTmAf8A\nbrR9dcn3fuB4222SWoBfA++wPbukHwLsYvvjkj4BfKGcPyJptdL+rWzPkbQnsL/to0re24EHgFnd\nvUkBGLnJKK9y0Iox2iqTlJdNe3s7bW1tjW5GLKP0X/NLHza39F9zS/81F0mLDRD6Y4jR7PLZWnvR\n9jzbPwfuoXqQvgyYtYRy/g4cUyY7twGDSzkPAneWv07TgXXL8QhgTduvlPOnqSZHH0Y1afpnNfn+\nWnP8duBvncFBcRNwmKRVbH+9pD9S2vEK8CTV2wKo3lj8pSbv88CdiwsOIiIiIiJWBH0eINj+HdV/\nzj8qadDSbl9COc8Bw4CzgAd7ULVKvheApyRtUq7vCNwGrA2s1nlfNxYCr3ZzbVD5W2K9wM3AdgCS\nVqUa2jS1B+2OiIiIiGiY/pqkfCjVvICLysNyrVHA3HI8G1i7DCECGEt5GJe0FjAF+BwwtLqkVcsb\nhaU5AzhJ0m7AA7YvsP0icD9w1GLy/A/wWkmvrbm2N/AD2/N7UOcM4B5JRwP7AQfb/mMP8kVERERE\nNEy/LHNq+1FJWwEnAz+UdDfwDLAGsC2wT7mvQ9IFwFRJ9wLXAn+VdCBwLzAc+DjVpOEOquVRv081\nefhgSc+UKncF1i/zFlaleuuwv+0/dGnaB4HvlXkSdwDrA5tKGm/7dkkHAMdLmgqsSTVM6hMlgDkY\nGC7pQ1SByy7AJsBBki6kCmT+STU34h89+Z2GDh7EjIz9j4iIiIgG6reN0mz/BTi9m6TvdbnvTODM\nmks31ByvX3O8JVSvEWyPLZORcTXr+rDaMiVdBEyT9BTVMKFZwKfK8Keda+4bBHy+lNE5PGpid99H\n0g9sX17qN/D/gJE16V8AfgQ8JulPVEOPbgM+XZZ2jYiIiIhY4fTXEKM+U/Mw787jWpLaqCYsD7e9\nPbAD8FXgi92UtaC7MpZW72JuORX4L9sjbb+FahnUNaiGKUVERERErJCaPkDogaOplkpdAIse6B8E\nftVXFZb5EvvZvrfzmu25VJOUH+2reiMiIiIille/DTFqoFOAj0kaSTVvYSEwhOotQp+w/bKkMyV9\niiogmE812fph20/0Vb0REREREctrwAcIZWJyd3Mf+rren/Z3nRERERERy2tlGGIUERERERE9NGAD\nhNpN2brZeyEiIiIiIroxkB+cN5a0N3Ae8H5JNwGPAzvZfrY/GyLpLcDXy2pGizV3/gJaT7uxT9sy\nM/ssRERERMQSDNg3CLZ/T7XR2jzb15fdj3ft7+CguB84oAH1RkRERETUZSC/QfgXtp9sUL2vAk83\nou6IiIiIiHoM2DcIXUlaT9JlklrL+eskfV7SZyTdLGnNcv0tks6XdJSkSyT9TtLBNeW0lDzjJR0j\naUNVDpU0UdJ+kt4o6ZPlWoukN0u6ojHfPCIiIiKi59TDjYObUgkGHrHdImlb4CZgR9szy5yEw23/\nSdIPgG8C9wGXAKOBd9t+UdKbgcm2x5Yyz6Laz+AHklqohg/dBNwIfIpqWNM3gI8B37K9UNIHgLNs\nt3bTxgnABIDhw0eMPeP8i/vq5wBgzIbr9Gn5K7uOjg5aWloa3YxYRum/5pc+bG7pv+aW/msu48eP\nv8/2uO7SVpohRranSXqs5tLpJTgYDWwIDLY9T9IlVIHDiyXfdEnr1uTbGri9pHVIWhuYWIKJe4A7\ngBHAF2wvLPf9uAQW3bVrEjAJYOQmo3zew33bJTMPaevT8ld27e3ttLW1NboZsYzSf80vfdjc0n/N\nLf03cKw0Q4y6MV3SRGAjYOZS7lXN8fXAjgCSNgFm1QQTLwFfAv4NWL+X2xsRERER0edWhgBhcWOo\nvgJMB24DRgKSNKQH5V0JvEHS+6gChd06EyRtCvwJ+CgwRdIay9PwiIiIiIj+NtCHGAmYI2kV4F3A\npsDeki6l+g///lQBxN3AF4HTgb2BsZL2ohou9G/ACEl72f4Z1RyDzwO32F6wqCJpf+B44CTgGeBV\n4EpJHwPeAbxW0u62b11cY4cOHsSM7FMQEREREQ000AOEVamGAC2UdDvVm4JVgYW296+57wqoXiEA\nv7R9iiS5msE9ufx1OhS4odw/hyoQuIjqzcI1wGBgAfD2cv8g4EfA5cBqffItIyIiIiJ6yUAPENam\nPMzbfqVcm7+4m12zpFPtcaeyatEJQJvtP5Vr6wFXAdeWNwoLumRbWHP8z2X4DhERERER/WbAzUGQ\nNEjSiHI6lmrZ0t7yDmCVzuAAwPYLwK3Ay71YT0REREREQwzENwhbAzdL+hpwm+3nerHsm4Axko7k\nf+cZDAUu6VzSNCIiIiKimQ24AMH2A8B6fVT2QuDsvig7IiIiImJFMOCGGEVERERExLJLgBARERER\nEYs0dYAgaVD5lKTVaq6rLFlK7fWIiIiIiFiypg0QSnCwt6RngQeBnWqShwD7SPod1cZnERERERHR\nA007SbnsOXCdpNnAL4C/16TNk7QA+KDt+xrVxoiIiIiIZtO0bxA62f4f4CvA9yStDiDpDcA6CQ4i\nIiIiIurT9AFC8TlgHvBfZejR+23/CEDS7pI6JLVKWkfSYZLmSmot6XtJ+rykEyRNlvQ7Se8saWtK\n+oakfSV9SdKtktprApEWSZ+T9ClJv5C0Qbm+uaRLJB0s6VuSHpV0UgN+l4iIiIiIush2o9vQKyS9\nCfgNcBHwBdt/q0mbCbTZnll7DnQAlwPzgYNsz5W0F/AR2/uXQOEq4ATbk0veKcBk29dLugS4yPZU\nSV8Eptv+gaRzgf2Bd9p+WtIw4CHbG3bT7gnABIARI0aMnTJlSq//NtF/Ojo6aGlpaXQzYhml/5pf\n+rC5pf+aW/qvuYwfP/4+2+O6S2vaOQhd2f6tpEuBtWqDg6Xk+YukHwOttueWy9OBdUv6HZIeBu6s\nybYoHfiG7QckbQRsDjxern8dGGf76VLObEnzF9OGScAkgNGjR7utra1nXzhWSO3t7aQPm1f6r/ml\nD5tb+q+5pf8GjgETIBSzgeHdXK/3NYl6mD5N0inAU8CjddYREREREbHCGShzEJbmz8B6UM0PAFqA\nQb1Q7iephmn9FHhjVbyG9EK5ERERERENMSAChDJZeH9gT6BN0n9Iqn2TMJFqlaMpwGjgt8BBkt4I\n7Fry7FLmChwAbCppZ0njgVbgCEkbStoG2BHYvUxI3gDYQ9IHgGnAicAepYxRkg6SNFjSfsBwSYd2\nbuAWEREREbEiGhBDjGx3AFeWv+7Sfwb8rObS9VD9ux/4kG1LkqsZ2+eWP8q11s6HetvPUAUhnU7s\nUtUFJd8Nts+tKfMaqrcWERERERErtAERICwr1yzhVHvc9Vp3aT0pt958ERERERGNNiCGGEVERERE\nRO9IgBAREREREYskQIiIiIiIiEUSIERERERExCIJECIiIiIiYpEBFyBIGlRzvFKv0hQRERERUa8B\nFyAAG0s6XtKrwHvKRmUzy8ZmERERERGxBAMuQLD9e+BaYJ7t623PB3a1/WyDmxYRERERscIbcAFC\nd2w/2eg2REREREQ0gwEfIEhaT9JlklrL+eskfV7SZyTdLGnNcv0tks6XdJSkSyT9TtLBNeW0lDzj\nJR0jacOa62dLOkjS1ZI2k9Rayp5Y7tlN0h2d5xERERERKyrZbnQbel0JBh6x3SJpW+AmYEfbMyXd\nBBxu+0+SfgB8E7gPuAQYDbzb9ouS3gxMtj22lHkW8LDtH0hqAe4v5d4F7G57gqTXAa+1/VhnMGB7\nYsn/f85r2jplaqcIAAAaSklEQVQBmAAwYsSIsVOmTOmjXyX6Q0dHBy0tLY1uRiyj9F/zSx82t/Rf\nc0v/NZfx48ffZ3tcd2kDfpUf29MkPVZz6fQSHIwGNgQG254n6RKqwOHFkm+6pHVr8m0N3F7SOiSt\nDUwEBgGfk3Q9cI7tO+ts3yRgEsDo0aPd1ta2TN8zVgzt7e2kD5tX+q/5pQ+bW/qvuaX/Bo4BP8So\nG9PLf/M3AmYu5V7VHF8P7AggaRNgVgkm/gJsA1wOXFIzLGngvZqJiIiIiAFvIAcIi3tA/wowHbgN\nGAlI0pAelHcl8AZJ76MKFHYr198HvMH2T4BDgLeW638G1qOqYAiwJdXbhoiIiIiIFdZADRAEzJG0\niqR3A5sCe0taA1gf2B84ALgb+CLVA//ewFhJe0laU9KhwAhJe5Uyr6UKEm6w/UPbL5XrvwMukPQB\nYAeqAATgh8DWkm4FPgU8Amwu6U19+9UjIiIiIpbdQJ2DsCrVEKCFkm6nelOwKrDQ9v41910B1SsE\n4Je2T5EkVzO3J5e/TocCN5T75wCvAhfZ/j7w3q4NsP03YJfe/2oREREREX1noAYIa1Me5m2/Uq7N\nX9zNrlnKqfa4U1m16ASgzfafyrX1gKskXVvzNiEiIiIioqkNmCFGkgZJGlFOx1ItW9pb3gGs0hkc\nANh+AbgVeLkX64mIiIiIaKiB9AZha+BmSV8DbrP9XC+WfRMwRtKRwDNUw4uGApfYXtiL9URERERE\nNNSACRBsP0BZNagPyl4InN0XZUdERERErEgGzBCjiIiIiIhYfgkQIiIiIiJikQQIERERERGxyICZ\ng7A4kjYDPgEcB3ya/111aFC5vqPt2YvJOwyYBmxie76k84GnbF/Q9y2PiIiIiOh/Az5AsP24pKuB\n42x/uTZN0mxgwRLyzpa0r+3OPRS+BPyj71obEREREdFYAz5AWIqfsoQN1ABsT6s5fqHPWxQRERER\n0UDqZuPgAUdSG3C7bdVc2xN4FDgeGGe7TdIY4Bhgi3I+AjgHOBOYBRwMbGj7nFLGscAQ4O3AN2zf\nIum1wHeA84D3AzsBs2wftJi2TQAmAIwYMWLslClTev37R//p6OigpaWl0c2IZZT+a37pw+aW/mtu\n6b/mMn78+Ptsj+subaV6gyDpAzWnhwMfAG4AxgHYfljSj4GJ5Z4tgD2oAoQWYF/gsVLWfwBDbJ8r\n6UHgIOAWYDywD/BV25+UJOAeSWNsP9y1TbYnAZMARo8e7ba2tt78ytHP2tvbSR82r/Rf80sfNrf0\nX3NL/w0cK1WAYPvHnceS/tqD+++U9Hg5/pukm4DWknwf8JSkFuAtwOBy31WSnrV9Zzm3pN8C6/bq\nl4mIiIiI6AMrVYBQy/bNAJKWaYyV7d9K2g/YFJgKbLaULFpKekREREREw2UfBPgzsF7N+fZUS6Au\nkaQdgSNsnwesX13SkL5pYkRERERE/xjwAYKkTYHdyvH+kjaqTbc9Hbhb0r2Svga8AKwiafcu5bwJ\n2B3YvpS5ETBa0oeBvwLvBI6Q9D5gmKRjJK0r6W3A1sC+ZQJzRERERMQKa2UYYjQTOMP2Zxd3g+0j\nu1y6vOstwBPAoVRDhVa1/QTVMqmdrgOQtIrttSTJ1RJRv6J6KxERERERscIb8AGC7cVuhNZDqwEv\n2H6ls0jglcXdbHth+Rz468dGRERExIAz4IcYLQ9JQ4EHbc9tdFsiIiIiIvpDAoQl2w04vdGNiIiI\niIjoLwN+iNHysH1Do9sQEREREdGf8gYhIiIiIiIWaXiAIGmQJJXjwY1uT0RERETEyqxfAgRJe0i6\nXtIvJa3VJXkYsJekK4ExSyhjQ0lPJYiIiIiIiOg7/TIHwfYtkgxcBtwgac/OlYFsvwDcKGmE7fuX\nUMyzwG625/d9iyMiIiIiVk79OcRoPvB+qjcG10gaUk9mV57sk5ZFRERERATQ/6sYvQCMB34B/ETS\nAbZfrb1B0iDgg8DfgBHApsBngZHAt2zvJWld4NPAc8C6wDZAK/AfwAeA0cCGwEG2Z5Zy9wRWp9r4\nbBdgIvAycArV24lWqh2PNwLeY/v5ku9twNZUOylvXtrgknZ4aaeAhbavlfRmqp2Yv2b7Mkn7AV8E\n/tv2Zcv/E0ZERERE9J1+X+bU9p8l7UoVJFwu6d87dx8ujivt+gtVALAd1cN+K7BruefvwAZAC/Bx\n25b0daqg4YO2F0g6Fvg4cKqkcVSBw4+BeVSBytjy+RHgMtsTASSdAxwEXFgmT08G3mz7FUmbAFdK\nmgecVep6d8l3uaQ9gJeAh2q+7zUlSOiWpAnABIARI0bQ3t5e1+8ZK5aOjo70YRNL/zW/9GFzS/81\nt/TfwNGQfRBs/6UmSLhE0kdqkg8CPmz7sXJ+U/mcJelPJf8/Jf0OmNn533zgfmCk7QXl/BGqNwIA\n+wP32L6pS5lIuhO4s6b+6cAby/EIYE3br5Tzp4FBtv9d0kHAizX5ZgHP2/6qpMvq+C0mAZMARo8e\n7ba2tp5mjRVQe3s76cPmlf5rfunD5pb+a27pv4GjYcuc2p5NtVPxdsCFNUlDgC2XociFXc5NNfRn\nWcpUaeMLwFPlzQHAjsBt5fhOYJSkziBrLPDLmrojIiIiIppOQ/dBqAkSdqIMswFuBM6QNAxA0khJ\nyxIw1LoROFzStqXMoZLaepj3DOAkSbsBD9i+oFz/M/A9qiFM+wKn276vJm29Utc6VPMoBi3nd4iI\niIiI6HP9MsSoPFwfDjwu6R7bt3Sm2X6xpF9cLn2JaqLwg5KmAv8P+G4Zxz9c0vuBqcDOwJvKEKEh\nwAHAUEljqOYWHACMlrSx7V9ImghcL+lx4F7gC5J2oNp74WBJz5T6dwXWlzSK6vc5C9jf9h+6fK0j\ngW2Bk22/1CXtm8BVJQi5GXgQ2EHSLbb/uEw/YkREREREP+ivfRB+QTXfYHHpf6V6oKfsj/Dh2nRJ\nq1C9BVgLGEw1BGhvqmFFg8r5v5XzVamWVD2+XB9Uyj0POK9LuVNtj+3cybnMZzisyz0XAdMkPVXK\nnwV8CvgO1bCixyTNKnXdB5xUVk7anoiIiIiIJtOQScr1Kqscdc4xeKVL8qt1nteW69rPrsobgHWB\n4WVlJAHvoFq29C7gattHlXsHAydRrYr0taV8pYiIiIiIFVJTBAgNdDRwbufKSGU51QeBXwHHAlt0\n3mh7vqT7qZZRjYiIiIhoSgkQluwU4GOSRgIdVG8xhgBfpVpW9TMlKOh8q9Fh+38a0tKIiIiIiF6Q\nAGEJysTk0xeT3F7+IiIiIiIGjIYucxoRERERESuWBAgREREREbHIShcgSHqNpAskfajRbYmIiIiI\nWNEM6DkIknYFtgP+BowGXgamANsAD/RjO04ERto+sb/qjIiIiIhYFgM2QJA0HDjR9r41175ge4ak\n9n5uzncZwL91RERERAwcA3mI0YbAGEmvr7l2diMaYvsl27MbUXdERERERD0G8n+1HwIeBB6VdDZw\noe2Xa9LXkHQasD2wMXBAWdYUSYcC6wNjgZ/Z/r6kNYFzgJuAtwFvofr99gTWAA4BXgvcAAwC3gNM\nBX4OvBvY3fYn+/YrR0REREQsH9ludBv6jKRVqHY8/izVZmYn2f6xpIlUcxI+bHuepI8Cm9g+VdI7\nqIKF4yRtBnzT9rskvRO4CjjB9uRS/hRgsu3rJb0R+CXwfuBPwNtt/0TS6sBZwGtsH95NGycAEwBG\njBgxdsqUKX34i0Rf6+jooKWlpdHNiGWU/mt+6cPmlv5rbum/5jJ+/Pj7bI/rLm0gv0HA9kLgAkmX\nUm14NlnS8yX5ZtvzyvEMYMdyPAv4rKTVgF2AwaWsOyQ9DNxZU8V0YN2S/gdJ+wE/BP7b9nfL9XmS\nrgEOX0wbJwGTAEaPHu22trbl/t7ROO3t7aQPm1f6r/mlD5tb+q/5zJ8/n1mzZjFv3jzWWWcdVl99\n9UY3KbpYffXV2WijjRg8eHCP8wzYAEHSDsBjtl+2PQc4XZKpVjXqNguA7Scl7QK8C/gpsLTlUNV5\nYPsBST8FPizpctuvLPcXiYiIiFhBzZo1i7XWWovW1lY6OjpYa621Gt2kqGGb2bNnM2vWLDbeeOMe\n5xvIk5RHAyd0uTaYahjQYknaGDgXOJPq7YAkDelJhZJ2Ay4GrgcurLfBEREREc1k3rx5DBs2DElL\nvzn6nSSGDRvGvHnzln5zjQH7BoFqn4MDJX0TuB8YAtwF/AMYB2wl6RHgceC95XwbqgnHGwAfpRp6\nNJLq7cMdQCtwhKRvA8OphiWNknQ7sC/VW4djgZuBOyT9Dbi0pG0haSvbj/THl4+IiIjoDwkOVmzL\n0j8DNkCw/Sjwvq7XJQ0C9rVtSYNsLwBO6nLbyJrjjUs+2W5V+ZVtP0O1glFnmd8BvkW1gtGfqFY0\nWpVqCNIpgCnzGSIiIiIiVlQDNkBYnBIQ/MtxD/K59rObMueW09oy53e5NXMSIiIiYsBqPe3GXi1v\n5ll792p5SzJt2jSeffZZ9tprryXe197ezrnnnssNN9zAddddx/Tp0znttNO45ppr2HzzzXnzm9/c\nZ23sjzpgYM9BiIiIiIhYqldffZVp06bxs5/9rK58733veznttNOA6uF9+vTpy92WBQsW///r3qpj\naRIgRERERERTmjlzJltssQWHH344m2++OYcccgi33norO++8M5ttthn33nsvL774Ivvttx9bb701\nO+64Iw899BAAEydO5NBDD2XnnXfm0EMP5YwzzuAnP/kJ2267LT/5yU+49957edvb3sZ2223HTjvt\nxIwZM/6l/ssuu4xPfOIT3H333Vx33XWccsopbLvttjzxxBNsv/32i+57/PHH/895V62trZx66qls\nv/32XHHFFVx88cXssMMObLPNNuy///784x//6LaOJ554gj333JOxY8fy9re/nccee6xXfteVbohR\nRERERAwcv//977niiiv47ne/yw477MAPf/hD7rrrLq677jq+9KUv8YY3vIHtttuOa665httuu43D\nDjuMadOmATB9+nTuuusuhg4dymWXXcbUqVP5+te/DsCcOXO48847WXXVVbn11lv59Kc/zZVXXtlt\nG3baaSfe+973ss8++3DAAQcAsM466zBt2jS23XZbLr30Uj784Q8v8XsMGzaM+++/H4DZs2dz1FFH\nAfCf//mffOc73+HYY4/9lzp22203LrroIjbbbDN+/etfc/TRR3Pbbbct92+aACEiIiIimtbGG2/M\nmDFjANhyyy3ZbbfdkMSYMWOYOXMmf/jDHxY92O+6667Mnj2bOXPmANUQoaFDh3Zb7ksvvcSHPvQh\nHn/8cSQxf37XqaVLduSRR3LppZfyla98ZdEbif/f3t0HR1WdcRz/PryYVUhAIcxQ4tQIloKWF1Gh\nrUyNRWLrWxkUUqhCadVi9Z++WFGYMcIf2qGjUjvTcWqVtvgGNojj6GBHM75QtWJBcSItkTiNdirG\nIU1UMJSnf9yz67rmbcnuZi/5fWbu5O6955x7Lg8Hcvaec093Fi5cmNrftWsXK1euZP/+/bS3t1Nd\nXf259O3t7Wzbto3LLrssdezgwYNZ1bEr6iCIiIiISGyVlHy6XNWgQYNSnwcNGsShQ4e6XUF42LBh\nXZ5btWoVVVVV1NXV0dTUlPUq3/Pnz6e2tpZzzz2XGTNmMGrUqG7Tp9dl6dKlbN68malTp3LfffdR\nX1//ufSHDx9m5MiRqachuRSrOQhmdq2ZDe/mfKWZPWNmJxWuViIiIiJSrGbPns2GDRuA6A1Eo0eP\npqys7HPpSktLaWtrS31ubW1l3LhxQDTXoCeZ+ROJBNXV1SxfvrzH4UWZ2traGDt2LB0dHam6Z16j\nrKyMyspKNm7cCESrJu/cuTOr63Qlbk8QFgFDzOz9tGMJ4A6ilYu3Al/OtlAzGwXsAE529w4zuwPY\n6+535qDOIiIiIgNCIV9L2ls333wzy5YtY8qUKRx33HGsX7++03RVVVXceuutTJs2jRUrVnD99dez\nZMkS1qxZwwUX9HxfNTU1XHnllaxbt45NmzYxfvx4Fi9eTF1dHXPnzs2qzqtXr2bmzJmUl5czc+bM\nVKcg8xobNmxg+fLlrFmzho6ODmpqapg6dWpW1+qMdfJa/6JkZpXACe6+PeP4vUSLmc1x90NmVg8s\ndfemLMuf5u47wv4Y4CN3b89J5Xtp4sSJ3tkMeYmP+vr6rB9BSvFQ/OJPMYw3xS9+GhoamDRpEhB9\n611aWtrPNSoua9eupbW1ldWrV/drPdLjlGRm2939jM7Sx+YJgrvvBfamHzOzq4G5wOnufqiP5e9I\n23+vL2WJiIiIyMA2b948Ghsbc/JWoUKLzROETGZ2JvA0UO3u29KO1wO1RB2HGcBHwKXJDoSZXUq0\nonFpOH9j2P9lyNcMLATGufsvQ57rgBJgNvAbd99qZscD9wC/AuYBXwOa3X1BWl2WAvsBAw67+6Od\n3MdVwFUA5eXlMx5++OEc/OlIf2lvb2f48C6nyUiRU/ziTzGMN8UvfkaMGMGECROAaIGvwYMH93ON\nituiRYt4++23P3OstraWOXPm5PW6e/bsobW19TPHqqqq4v8EIV2YM7AJuDG9c5BmqruvCGkfAM4D\nnjCzecAs4C9AC3CQaM5CKVGHohYYDlwEvBnyfw8ocfe1ZrYTWEA016EKuBC43d1/ZmYGvGhmX3H3\n181sMvBdd68O5fzJzOYCre5+Y7Ki7n43cDdEQ4z0aDXe9Hg83hS/+FMM403xi5+GhobUsCINMerZ\nY4891i/XTSQSTJ8+vdfpY9dBMLNBwP3Ac+7+6y6SbU7b3w2MCfsLgPXu/mT4nPyJmf0TwN33m9mT\nwEnh1HZgb3h70lnA0JDuz2b2rrs/Fz67mTUAJ4R8pwEfpNWjGfiPu9+e5S2LiIiIFC13J/qeVIrR\nkYwWitVrToNbgLGEYTlJZlZuZid0noXk39oS4NRsLubuDcD5wNXAK73IkrzWc8AEM0t2wmYAz2Zz\nbREREZFilkgkaGlpOaJfQiX/3J2WlhYSiURW+WL1BMHMLgSuAc5y948yTi8AHu+hiMeBWjN7xN2b\nQofiFHd/qZtrzgKWufvFZrYkOmQl7t7TUnX7gPXAL8zsNWBF5huYREREROKsoqKC5uZm9u3bx4ED\nB7L+RVTyL5FIUFFRkVWe2HQQwmtO/wg8BZxjZucQPQFJAF8Cfgh8DJwILDOz3xHd39eBSjPbCtxL\nNOfghfBL+/PAbRnXmQTMAcrMbDxQAUw0s+8TzVv4Rij/XWCUmf0YeACYCEwBLgpzFRYC04Cfuvtn\nZ4WIiIiIHAWGDh1KZWUlEM0hyWacuxSv2HQQwmtOj+8mybVmNtjdfx8mDJu7HyaaoJzu52Hr9DJA\nI3A50VChIe7eSDQhOmkLRHMh3L3UzMyj52p/BU5PJjKze4iGFb1pZs2hvO3AT9z9w97dtYiIiIhI\nYcVxDkKX3P1/4aeHzkE2jgHec/dPkvnd/ZNurnU4ea0uklwD1Ln7WHc/E/gq8BbwgyzrJSIiIiJS\nMLF5gpBPZnYssNPdP85hsdcRDWcCwN07zOxV4EAOryEiIiIiklOxXSgtl8Lk5+fdfX8OyzyHaL7C\nq0QLswG0u/sL3eRpI3otq8TXaOD9/q6EHDHFL/4Uw3hT/OJN8YuXL7p7eWcn1EEoImb2Slcr2kk8\nKIbxpvjFn2IYb4pfvCl+R4+jag6CiIiIiIj0jToIIiIiIiKSog5Ccbm7vysgfaYYxpviF3+KYbwp\nfvGm+B0lNAdBRERERERS9ARBRERERERS1EHIIzM738x2m9keM7uhk/MlZvZQOP+SmZ2Udm5FOL7b\nzKp7W6bkTp7i12Rmr5vZDjN7pTB3MnAdaQzNbJSZPWNm7WZ2V0aeGSGGe8xsXVi5XfIgT/GrD2Xu\nCNuYwtzNwNOH+J1nZttDO9tuZuem5VH7K6A8xVBtMA7cXVseNmAw0AicTLRK805gckaaa4Dfhv0a\n4KGwPzmkLwEqQzmDe1OmtuKNXzjXBIzu7/sbCFsfYzgMOBv4EXBXRp6XgVmAAU8A3+rvez0atzzG\nrx44o7/v72jf+hi/6cAXwv5pwDtpedT+4h9DtcEYbHqCkD9nAXvc/S13/wR4ELgkI80lwPqwvwn4\nZvg25BLgQXc/6O57gT2hvN6UKbmRj/hJYR1xDN39Q3d/noyVz81sLFDm7i969D/dH4Dv5PUuBq6c\nx08Kqi/x+7u7vxuOvwEcG76pVvsrrJzHsCC1lpxQByF/xgH/SvvcHI51msbdDwGtwKhu8vamTMmN\nfMQPwIGt4ZHrVXmot3yqLzHsrszmHsqU3MhH/JLuDUMbVmmISt7kKn7zgVfd/SBqf4WWjxgmqQ0W\nuSH9XQGRAeZsd38njLl8yszedPdn+7tSIgPI4tAGS4FHgMuJvomWImNmpwK3AXP7uy5yZLqIodpg\nDOgJQv68A5yY9rkiHOs0jZkNAUYALd3k7U2Zkhv5iB/unvz5HlCHhh7lU19i2F2ZFT2UKbmRj/il\nt8E24H7UBvOlT/EzswqifyOvcPfGtPRqf4WTjxiqDcaEOgj58zfgFDOrNLNjiCbvbMlIswVYEvYv\nBZ4O4yq3ADVhzGUlcArRxKzelCm5kfP4mdmw8I0JZjaM6BuVXQW4l4GqLzHslLv/G/ivmc0Kj8Wv\nAB7NfdWFPMTPzIaY2eiwPxS4ELXBfDni+JnZSOBx4AZ3fyGZWO2v4HIeQ7XBGOnvWdJH8wZ8G/gH\n0VsAbgrHbgEuDvsJYCPRJNaXgZPT8t4U8u0m7S0NnZWpLR7xI3oTxM6wvaH4FX0Mm4APgHaisbeT\nw/EziP5DawTuIiw4qa3440f0dqPtwGuhDd5JeMOYtuKJH7AS+BDYkbaNCefU/mIcQ7XB+GxaSVlE\nRERERFI0xEhERERERFLUQRARERERkRR1EEREREREJEUdBBERERERSVEHQUREREREUtRBEBERERGR\nFHUQREREREQkRR0EERERERFJ+T/LmJs0DOxsaQAAAABJRU5ErkJggg==\n","text/plain":["<Figure size 864x576 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"vACHWvB_Ogi6","colab_type":"text"},"source":["The above plot only shows the rate, but not the \"severity\".  So try adding the cumulative confirmed cases, and the 7-day trending info"]},{"cell_type":"code","metadata":{"id":"RkLgLsVwuHpy","colab_type":"code","outputId":"3dc0855e-a180-46ec-a5aa-5bc6caebab5c","colab":{"base_uri":"https://localhost:8080/","height":255},"executionInfo":{"status":"ok","timestamp":1582303063360,"user_tz":360,"elapsed":475,"user":{"displayName":"","photoUrl":"","userId":""}}},"source":["ma = province.reset_index('province_name_en').groupby('province_name_en')['new_confirmed', 'new_dead'].rolling(5, min_periods=1).mean()\n","# ma from above is indexed by (province, date), which is different order than province's (date, index)\n","# so direct assignment will result in NA, need to swaplevel first\n","ma = ma.swaplevel()\n","province['new_confirmed_MA'] = ma['new_confirmed']\n","province['new_dead_MA'] = ma['new_dead']\n","\n","# The next two columns are mainly for plot rendering\n","province['new_confirmed_logMA'] = np.log10(province['new_confirmed_MA'] + 2)  \n","province['new_dead_logMA'] = np.log10(province['new_dead_MA'] + 2)\n","\n","province.loc[(slice(None), 'Hubei'), :].tail()"],"execution_count":15,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th></th>\n","      <th>zip_code</th>\n","      <th>cum_confirmed</th>\n","      <th>cum_cured</th>\n","      <th>cum_dead</th>\n","      <th>new_confirmed</th>\n","      <th>new_cured</th>\n","      <th>new_dead</th>\n","      <th>mortality_rate</th>\n","      <th>new_confirmed_MA</th>\n","      <th>new_dead_MA</th>\n","      <th>new_confirmed_logMA</th>\n","      <th>new_dead_logMA</th>\n","    </tr>\n","    <tr>\n","      <th>update_date</th>\n","      <th>province_name_en</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>2020-02-17</th>\n","      <th>Hubei</th>\n","      <td>7187536.0</td>\n","      <td>58182</td>\n","      <td>6693</td>\n","      <td>1696</td>\n","      <td>1933.0</td>\n","      <td>1027.0</td>\n","      <td>100.0</td>\n","      <td>0.029150</td>\n","      <td>4963.2</td>\n","      <td>125.6</td>\n","      <td>3.695937</td>\n","      <td>2.105851</td>\n","    </tr>\n","    <tr>\n","      <th>2020-02-18</th>\n","      <th>Hubei</th>\n","      <td>7187536.0</td>\n","      <td>59989</td>\n","      <td>7943</td>\n","      <td>1789</td>\n","      <td>1807.0</td>\n","      <td>1250.0</td>\n","      <td>93.0</td>\n","      <td>0.029822</td>\n","      <td>2356.6</td>\n","      <td>95.8</td>\n","      <td>3.372654</td>\n","      <td>1.990339</td>\n","    </tr>\n","    <tr>\n","      <th>2020-02-19</th>\n","      <th>Hubei</th>\n","      <td>7187536.0</td>\n","      <td>61682</td>\n","      <td>9336</td>\n","      <td>1921</td>\n","      <td>1693.0</td>\n","      <td>1375.0</td>\n","      <td>132.0</td>\n","      <td>0.031144</td>\n","      <td>1939.2</td>\n","      <td>120.6</td>\n","      <td>3.288070</td>\n","      <td>2.088490</td>\n","    </tr>\n","    <tr>\n","      <th>2020-02-20</th>\n","      <th>Hubei</th>\n","      <td>7187536.0</td>\n","      <td>62031</td>\n","      <td>10521</td>\n","      <td>2029</td>\n","      <td>349.0</td>\n","      <td>1197.0</td>\n","      <td>108.0</td>\n","      <td>0.032709</td>\n","      <td>1525.0</td>\n","      <td>114.4</td>\n","      <td>3.183839</td>\n","      <td>2.065953</td>\n","    </tr>\n","    <tr>\n","      <th>2020-02-21</th>\n","      <th>Hubei</th>\n","      <td>7187536.0</td>\n","      <td>62974</td>\n","      <td>11881</td>\n","      <td>2144</td>\n","      <td>723.0</td>\n","      <td>1348.0</td>\n","      <td>115.0</td>\n","      <td>0.034046</td>\n","      <td>1301.0</td>\n","      <td>109.6</td>\n","      <td>3.114944</td>\n","      <td>2.047664</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                               zip_code  ...  new_dead_logMA\n","update_date province_name_en             ...                \n","2020-02-17  Hubei             7187536.0  ...        2.105851\n","2020-02-18  Hubei             7187536.0  ...        1.990339\n","2020-02-19  Hubei             7187536.0  ...        2.088490\n","2020-02-20  Hubei             7187536.0  ...        2.065953\n","2020-02-21  Hubei             7187536.0  ...        2.047664\n","\n","[5 rows x 12 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\u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtmp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mprovince\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdatetime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2020\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m16\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreset_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mtmp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtmp\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mtmp\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'province_name_en'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m'Hubei'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m fig2 = px.scatter(tmp, \n\u001b[1;32m      4\u001b[0m                  \u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'cum_confirmed'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m                  \u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'mortality_rate'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mNameError\u001b[0m: name 'province' is not defined"]}]},{"cell_type":"code","metadata":{"id":"xNGN56uv_JAH","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"Fh9iFjLHXDQi","colab_type":"code","outputId":"9ed6d048-36a1-4faa-a7f6-778b87d68b54","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["py.plot(fig, filename='mortality_rate_by_region', auto_copen=True)"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'https://plot.ly/~jxu1/100/'"]},"metadata":{"tags":[]},"execution_count":39}]},{"cell_type":"code","metadata":{"id":"asx1eljYXOwE","colab_type":"code","outputId":"dc4879cf-e006-4b06-f5b3-dcc97788a199","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["py.plot(fig2, filename='new_confirm_by_region', auto_copen=True)"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'https://plot.ly/~jxu1/102/'"]},"metadata":{"tags":[]},"execution_count":41}]},{"cell_type":"markdown","metadata":{"id":"x6h27SavqQCT","colab_type":"text"},"source":["# Death rate by city within Hubei"]},{"cell_type":"code","metadata":{"id":"ggCdeQBoqS92","colab_type":"code","colab":{}},"source":["tmp = daily_frm[daily_frm['province_name_en'] == 'Hubei'].copy().set_index(['update_date', 'city_name_en'])\n","tmp['new_confirmed_MA'] = 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